An electronic nose for harmful gas early detection based on a hybrid deep learning method H-CRNN-Reference-Cited by-同舟云学术

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An electronic nose for harmful gas early detection based on a hybrid deep learning method H-CRNN

Published:2023-12 Issue: Volume:195 Page:109464
ISSN:0026-265X
Container-title:Microchemical Journal
language:en
Short-container-title:Microchemical Journal

Author:

Mao Guosheng,Zhang Yanmei,Xu Yang,Li Xiaoyu,Xu Min,Zhang Yiyi,Jia Pengfei

Funder

Sichuan Province Science and Technology Support Program

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Spectroscopy,Analytical Chemistry

Reference43 articles.

1. Electronic noses for food quality: a review;Loutfi;J. Food Eng.,2015

2. Feature extraction of citrus juice during storage for electronic nose based on cellular neural network;Cao;IEEE Sens. J.,2020

3. Intelligent detection of flavor changes in ginger during microwave vacuum drying based on LF-NMR;Sun;Food Res. Int.,2019

4. A low-power wireless multichannel gas sensing system based on a capacitive micromachined ultrasonic transducer (CMUT) array;Seok;IEEE Internet Things J.,2019

5. Computationally efficient weighted binary decision codes for gas identification with array of gas sensors;Hassan;IEEE Sens. J.,2017

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4. High-performance identification and real-time monitoring of calcium metabolite in urine with calconcarboxylic acid-based intelligent detection system;Microchemical Journal;2024-05

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